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_{"Mathematics is not about numbers, equations, or algorithms — it is about understanding."}

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👤 About Me

I am a mathematician and machine learning researcher passionate about principled, rigorous approaches to artificial intelligence. My work lies at the intersection of theoretical foundations and practical deployment — from clustering algorithms to distributed inference at the edge.

Driven by intellectual curiosity, I pursue genuinely difficult problems with a focus on precision, independence, and depth.

_{Previous web presence:   Site v1  |  Site v2  |  Current}

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🔭 Research Interests

🧩 Clustering & Multi-View Learning	Developing robust algorithms for unsupervised structure discovery across heterogeneous data representations.
🤝 Hybrid Learning Architectures	Bridging classical supervised methods with modern deep learning pipelines for improved generalization.
🌐 Federated & Distributed Learning	Privacy-preserving model training across decentralized nodes with communication constraints.
⚡ Edge AI & Cyber-Physical Systems	Deploying intelligent inference in resource-constrained, real-time environments.
🔍 Pattern Recognition	Statistical and geometric approaches to identifying structure in high-dimensional data.

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🛠️ Technical Skills

Languages & Frameworks

     

Areas of Proficiency

Domain	Competencies
Machine Learning	Supervised, unsupervised, and semi-supervised learning; model evaluation and selection
Deep Learning	Neural architecture design, optimization, regularization
Data Analysis	Statistical modeling, dimensionality reduction, visualization
Edge AI	Model compression, on-device inference, latency-aware deployment
Pattern Recognition	Feature engineering, classification, anomaly detection

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📜 Certifications

Certification	Issued	Credential	Issuer
Machine Learning Specialization	Oct 2022	View Certificate ↗	Coursera · DeepLearning.AI
TensorFlow Developer Specialization	Nov 2022	View Certificate ↗	Coursera · DeepLearning.AI

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🌍 Availability

I am open to global opportunities in machine learning research, edge AI systems, and distributed computing. My work combines strong mathematical foundations with practical, hands-on implementation.

📬 Contact: kristinasinaga41@gmail.com

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🌟 What Sets Me Apart

• Mathematical rigour: Analysing and designing models with precision beyond implementation.
• Independent thinking: Assessing problems on their merits rather than following trends.
• Resourcefulness: Treating constraints as design parameters, not obstacles.
• Depth of focus: Prioritising mastery and high standards in all output.

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🛡️ Current Status

  ■ Advancing research in distributed and federated learning
  ■ Preparing for new professional engagements (actively seeking new opportunities)

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_{"Rigour is not a constraint on creativity — it is its foundation."}